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Record W1984563449 · doi:10.1149/2.083308jes

The Impact of Potential Cycling on PEMFC Durability

2013· article· en· W1984563449 on OpenAlexaff
Hao Zhang, Herwig Haas, Jingwei Hu, Sumit Kundu, Mike Davis, Carmen Chuy

Bibliographic record

VenueJournal of The Electrochemical Society · 2013
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsAutomotive Fuel Cell Cooperation (Canada)
Fundersnot available
KeywordsCyclingDegradation (telecommunications)DurabilityProton exchange membrane fuel cellMaterials scienceVoltageDeposition (geology)MembraneAutomotive industryEnvironmental scienceChemical engineeringChemistryComposite materialThermodynamicsElectrical engineeringPhysicsEngineeringBiology

Abstract

fetched live from OpenAlex

Voltage cycling is one of the most damaging stressors for automotive PEMFC. Understanding of the effects of voltage cycling on performance degradation is crucial to improve PEMFC durability for automotive applications. This study focuses on the interaction between upper potential limit (UPL) and lower potential limit (LPL) on the stability of PEMFC. A well-defined peak of degradation rate is observed when the LPL is ∼0.8 V with UPL of 1.35 V. A mathematical model was developed to understand the observed relationship between degradation rate and lower potential. Modeling results suggest that when cycling to a lower potential of ∼0.8 V, almost all dissolved Pt migrate from the catalyst layer to the membrane with negligible re-deposition, resulting in a peak of degradation rate at ∼0.8 V. The amount of Pt in the membrane (PITM) measured at end of life (EOL) samples correlates with degradation rates and is in agreement with modeling results.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.204
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations55
Published2013
Admission routes1
Has abstractyes

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